my seminar project report

8/7/2019 My Seminar Project Report

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Seminar Project Report

In partial fulfillment for the award of the degree

Of

BACHELOR OF TECHNOLOGY

In

COMPUTER SCIENCE & ENGINEERING

Image Processing and Compression

Submitted By:

SANJEEV JHA

ROLL NO. 0701049

CSE- 8th

SEM



Candidate¶s Declaration

I hereby declare that the work presented in this project titled ³ Image Processing and

Compression ´ submitted towards completion of seminar -project in 8th

Semester of

B.Tech ( C .S.E.) at the Gurgaon college of engineering (GCE), Gurgaon.

I have not submitted the matter embodied in this project for the award of any other degree.

(SANJEEV JHA)



Acknowledgement

It is with the greatest pleasure and pride that I present this report before you. At this moment of

triumph, it would be unfair to neglect all those who helped me in the successful completion of

seminar.

First of all, I would like to place myself at the feet of God Almighty for his everlasting love and

for the blessings & courage that he gave me, which made it possible to me to see through the

turbulence and to set me in the right path.

The satisfaction that accompanies the successful completion of any work would be

incomplete without mentioning those people who made it possible, whose constant guidance and

encouragement rounded our efforts with success. It is a great pleasure for us to acknowledge the

assistance and contributions of great people to this effort.

I would also like to thank my friends who were ready with a positive comment all the

time , whether it was an off-hand comment to encourage me or a constructive piece of criticism.

SANJEEV JHA

(0701049)



Abstract

Project, aims to study ³image processing and Compression´ and develop new Image

Compression format.

An attempt is being made to demonstrate:-

1. Terms related to Image,

2. Image Compression Format,

3. Structure of Image

4. Demonstrate my own image compression format.

For developing or implementation of new image compression format I have used C#.NET(visual

studio). The output of this application is similar in structure but having different data section then

the original one so normal image viewer can¶t be used to open these files so for that a special

program is also developed to view these files.



Figures and Tables

Figure:-

Table Of Abbreviations:

ABBREVIATION FULL FORM

RGB Red, Green, Blue

tks Image file format

BMP BITMAP

1B,3B 1 Byte, 3Byte

MB.KB Mega Byte, Kilo Byte



Index

Content Page

Candidate Declaration««««««««««««««««««««««2

Certificate««««««««««««««««««««««««««..3

Acknowledgement«««««««««««««««««««««««.4

Abstract««««««««««««««««««««««««««..«5

Table and Figures««««««««««««««««««««««.«..6

1. Introduction«««««««««««««««««««««««.8

2. Structure of Image««««««««««««««««««««...9

a. Pixel view of image«««««««««««««««««9

b. Data storage in images««««««««««««««««10

c. Pixel content««««««««««««««««««««10

3. Image File Size««««««««««««««««««««««11

4. Type of Image Compression«««««««««««««««««12

a. Lossless compression««««««««««««««««...12

b. Lossy compression««««««««««««««««««13

5. One more image compression format«««««««««««««..16

6. Vector format«««««««««««««««««««««««17

7. Result««««««««««««««««««««««««««18

Reference«««««««««««««««««««««««««««.19



Chapter 1

Introduction

Digital image processing is the use of computer algorithms to perform image processing on

digital images. As a subcategory or field of digital signal processing, digital image processing

has many advantages over analog image processing. It allows a much wider range of algorithms

to be applied to the input data and can avoid problems such as the build-up of noise and signal

distortion during processing.

Image compression is minimizing the size in bytes of a graphics file without degrading the

quality of the image to an unacceptable level. The reduction in file size allows more images to be

stored in a given amount of disk or memory space



Chapter 2

Structure of Image

2.1 Pixel View of Image:-



2.2 Data Storage in Images:-

Every true color uses 3bytes to store pixel information and storage of each pixel starts from

upper left corner of the image and 3byte for each pixel is used.

2.3 Pixel Content:-

Every color that we have in light is produced through the combination of three primary colors

i.e., red, green, blue which we refer to as RGB. so in a pixel all three color has equal proportion s

but intensity may differ. So all three bytes are used to store color component of all three primary

color.



Chapter 3

Image file sizes

Image file size²expressed as the number of bytes²increases with the number of pixels

composing an image, and the color depth of the pixels. The greater the number of rows and

columns, the greater the image resolution, and the larger the file. Also, each pixel of an image

increases in size when its color depth increases²an 8-bit pixel (1 byte) stores 256 colors, a 24-

bit pixel (3 bytes) stores 16 million colors, the latter known as true color.

Image compression uses algorithms to decrease the size of a file. High resolution cameras

produce large image files, ranging from hundreds of kilobytes to megabytes, per the camera's

resolution and the image-storage format capacity. High resolution digital cameras record 12

megapixel (1MP = 1,000,000 pixels / 1 million) images, or more, in true color. For example, an

image recorded by a 12 MP camera; since each pixel uses 3 bytes to record true color, the

uncompressed image would occupy 36,000,000 bytes of memory²a great amount of digital

storage for one image, given that cameras must record and store many images to be practical.

Faced with large file sizes, both within the camera and a storage disc, image file formats were

developed to store such large images. An overview of the major graphic file formats follows

below



Chapter 4

Types of Image Compression

image compression formats minimize redundancy¶s present in the pixel data of the image for e.g.

If you have complete white image then also bmp use 2.24MB of storage for 1024 X 768

resolution image. But because the whole pixels are same then why don¶t we store only 1 pixel

because the rest are same that is what we are going to do to reduce the size of image file.

There are basically two types of image compression :-

1. Lossless Compression

2. Lossy Compression

4.1 Lossless Compression:-

Lossless compression algorithms reduce file size without losing image quality. In

Lossless image compression technique actual data is not lost rather redundant data is not stored

i.e., actual content of the image will remain and we could reverse the process to get original file

image back. There are no of method to do that for example using run length encoding, lampel

zip, lampel zip welse etc. some image compression format that does lossless compression are

BMP(run length encoding), gif,jpeg-ls(lossless).

Lossless compression is used where every pixel of data is important for us for examplefor medical purpose, for defence application, for GIS application like google earth, map window

GIS etc. even though it is used extensively using lossless compression technique compression

ratio achieved is very low in comparison to lossy compression technique because for a normal

file compression achieved using lossless compression is from 3:1 to 1.5:1 where as with lossy

compression format compression achieved is of the order of 20:1.



Lossless compression format are very less popular in daily use because the compression ration

achieved through lossless compression is very low in comparison to lossy compression format.

Therefore less emphasis is given on these techniques therefore not much progress is been

achieved in lossless compression techniques

4.2 Lossy Compression:-

In lossy image compression actual data is lost that is you can not reverse

the process to get original file back. It achieves better compression result then lossless

compression techniques some of the image format using image compression are jpeg, gif etc

lossy compression format reduces file size to greater extent then lossless compression but it does

it at the cost of actual data for example two most used lossy compression format are below:-

1. GIF(reduce the color depth)

2.

JP

EG - Encoding the Changes

1. GIF (Compuserve) - Reduce the Color Depth

GIF files compress images by two methods applied one after the other. Firstly, the palette is

picked, and has an upper limit of 256 colors (8-bit), but can be stored at a color depth of anything

from 8-bit to 1-bit. The entire graphical information is then further compressed using LZW

(Lempel-Ziv and Welch) compression, which is a lossless compression technique. Only the firstcompression method is important to the creator of the image, since it may require the color depth

to be reduced.



The GIF format is good for diagram-type images, and images which are already in 256 colors. It

can also incorporate transparency (where the area µbehind¶ the image can be seen through part of

the image), animation, and interlacing. Interlacing is the process by which the downloading of a

GIF can be streamed, so that it is does not have to be downloaded completely before being

partially displayed. A low-resolution version of the image can be presented before the full

higher-resolution version is downloaded. This is a feature designed specifically for use in Web

graphics.

A full color image The image in 256 colors

The image in 16 colors The image in 2 colors



2. JPEG - Encoding the Changes

JPEG files are a 24-bit alternative to GIF files. JPEGs use a µlossy¶ compression technique which

compares the next pixel value to the current one, and attempts to preserve the color gradient from

one to the next. Whilst the compression technique does not produce an image which is identical

to the original, it does retain the color depth. The full-color image above is an example of a JPEG

file.

This format does not, as yet, support transparency or animation. A form of JPEG called

Progressive JPEG does, however, allow for interlacing, and also has better compression than

non-Progressive JPEGs. JPEG is a good format for photographs, and other such images with

smooth color gradients. The format is not very good for line-art or diagram type images.



Chapter 5

One more image compression format

When you look at the actual image file structure of bitmap file you will find that all the data is

stored into the file whether we have redundant data or not i.e., all the pixels are stored whether it

contain same adjacent pixels so to avoid storing same pixels value again(which additionally

consume 3 bytes). I don¶t store same pixels value in my image file format that means (the last

pixels for us is left pixel) if the left pixel content is same as the current one we don¶t store the

value instead we keep moving right and store only those pixels that have different value. Now

the big question arises how do we know which pixel is which? Because we don¶t specify during

storage which pixel will corresponds to which coordinate value. So to avoid such problem I

additionally store 1byte for each pixel before the actual data so that we could know weather this

coordinate contain same value as previous pixel or different value, if value is same byte contain

true else it store false with 3byte of data. Using this technique and using the sample image I was

able to compress image upto 1.45:1.

In my present algorithm I have included 1byte scheme to know weather data is same to left pixel

or different but because this additional 1byte store more data so to minimize this additional data

we could use 1bite instead of 1byte because we just wanted to know weather it is same or not. By

doing so we are reducing file size more as for 1024X768 resolution pixel size consumed by 1

additional byte is 768 byte.



Chapter 6

Vector formats

As opposed to the raster image formats above (where the data describes the characteristics of

each individual pixel), vector image formats contain a geometric description which can be

rendered smoothly at any desired display size.

Vector file formats can contain bitmap data as well. 3D graphic file formats are technically

vector formats with pixel data texture mapping on the surface of a vector virtual object, warped

to match the angle of the viewing perspective.

At some point, all vector graphics must be rasterized in order to be displayed on digital monitors.

However, vector images can be displayed with analog CRT technology such as that used in some

electronic test equipment, medical monitors, radar displays, laser shows and early video games.

Plotters are printers that use vector data rather than pixel data to draw graphics.



Chapter 7

Result

5.1 Results:-

The Aim has successfully been implemented. The Main objective

Of this project is to achieve significant compression of image file and store them in a particular

directory with defined format. The compression achieved for the sample image is 1.45:1 i.e.,

original file size was 895KB and after compression file size become 619KB.

5.3 Future Extension

This result can be further improve to 2.49:1 by using 1Bite in place of 1 byte for storage of extra

information to the image.



Reference

Books:

Addison Wesley - Compressed Image File Formats.

Web:

http://www.mikety.net/Articles/ImageComp/ImageComp.html (Research on Lossless

Compression format)

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